多面体障碍物中点机器人的地形采集

N. Rao, S. Iyengar, B. Oommen, R. Kashyap
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引用次数: 54

摘要

研究了在固定多面体障碍物分布的未知地形中设置漫游点获取地形模型的问题。这个问题的动机是在完全获得地形模型后,可以实现从源点到目的点的无碰撞路径导航。这可以在不使用传感器的情况下通过应用现有的寻找路径问题的技术来完成。本文将点机器人自主机器(PRAM)作为现实生活中粗纱机器人的简化抽象模型。提出了一种算法,使PRAM能够自主获取未知多面体障碍物组成的未探测障碍物地形的二维/三维模型。在该方法中,PRAM利用其传感器对障碍物地形进行系统的探测,检测当前位置可见的所有边缘和顶点,并构建完整的障碍物地形模型。>
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On terrain acquisition by a point robot amidst polyhedral obstacles
The authors consider the problem of terrain model acquisition by a roving point placed in an unknown terrain populated by stationary polyhedral obstacles in two/three dimensions. The motivation for this problem is that after the terrain model is completely acquired, navigation from a source point to a destination point can be achieved along the collision-free paths. This can be done without the usage of sensors by applying the existing techniques for the find-path problem. In the paper, the point robot autonomous machine (PRAM) is used as a simplified abstract model for real-life roving robots. An algorithm is presented that enables PRAM to autonomously acquire the model of an unexplored obstacle terrain composed of an unknown number of polyhedral obstacles in two/three dimensions. In this method, PRAM undertakes a systematic exploration of the obstacle terrain with its sensor that detects all the edges and vertices visible from the present location, and builds the complete obstacle terrain model. >
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